Hypothesis in the context of Falsifiable

Cosmology (from Ancient Greek κόσμος (cosmos) 'the universe, the world' and λογία (logia) 'study of') is a branch of physics and metaphysics dealing with the nature of the universe, the cosmos. The term cosmology was first used in English in 1656 in Thomas Blount's Glossographia, with the meaning of "a speaking of the world". In 1731, German philosopher Christian Wolff used the term cosmology in Latin (cosmologia) to denote a branch of metaphysics that deals with the general nature of the physical world. Religious or mythological cosmology is a body of beliefs based on mythological, religious, and esoteric literature and traditions of creation myths and eschatology. In the science of astronomy, cosmology is concerned with the study of the chronology of the universe.

Physical cosmology is the study of the observable universe's origin, its large-scale structures and dynamics, and the ultimate fate of the universe, including the laws of science that govern these areas. It is investigated by scientists, including astronomers and physicists, as well as philosophers, such as metaphysicians, philosophers of physics, and philosophers of space and time. Because of this shared scope with philosophy, theories in physical cosmology may include both scientific and non-scientific propositions and may depend upon assumptions that cannot be tested. Physical cosmology is a sub-branch of astronomy that is concerned with the universe as a whole. Modern physical cosmology is dominated by the Big Bang Theory which attempts to bring together observational astronomy and particle physics; more specifically, a standard parameterization of the Big Bang with dark matter and dark energy, known as the Lambda-CDM model.

In its most common sense, methodology is the study of research methods. However, the term can also refer to the methods themselves or to the philosophical discussion of associated background assumptions. A method is a structured procedure for bringing about a certain goal, like acquiring knowledge or verifying knowledge claims. This normally involves various steps, like choosing a sample, collecting data from this sample, and interpreting the data. The study of methods concerns a detailed description and analysis of these processes. It includes evaluative aspects by comparing different methods. This way, it is assessed what advantages and disadvantages they have and for what research goals they may be used. These descriptions and evaluations depend on philosophical background assumptions. Examples are how to conceptualize the studied phenomena and what constitutes evidence for or against them. When understood in the widest sense, methodology also includes the discussion of these more abstract issues.

Methodologies are traditionally divided into quantitative and qualitative research. Quantitative research is the main methodology of the natural sciences. It uses precise numerical measurements. Its goal is usually to find universal laws used to make predictions about future events. The dominant methodology in the natural sciences is called the scientific method. It includes steps like observation and the formulation of a hypothesis. Further steps are to test the hypothesis using an experiment, to compare the measurements to the expected results, and to publish the findings.

Empirical evidence is evidence obtained through sense experience or experimental procedure. It is of central importance to the sciences and plays a role in various other fields, like epistemology and law.

There is no general agreement on how the terms evidence and empirical are to be defined. Often different fields work with quite different conceptions. In epistemology, evidence is what justifies beliefs or what determines whether holding a certain belief is rational. This is only possible if the evidence is possessed by the person, which has prompted various epistemologists to conceive evidence as private mental states like experiences or other beliefs. In philosophy of science, on the other hand, evidence is understood as that which confirms or disconfirms scientific hypotheses and arbitrates between competing theories. For this role, evidence must be public and uncontroversial, like observable physical objects or events and unlike private mental states, so that evidence may foster scientific consensus. The term empirical comes from Greek ἐμπειρία empeiría, i.e. 'experience'. In this context, it is usually understood as what is observable, in contrast to unobservable or theoretical objects. It is generally accepted that unaided perception constitutes observation, but it is disputed to what extent objects accessible only to aided perception, like bacteria seen through a microscope or positrons detected in a cloud chamber, should be regarded as observable.

The scientific method is an empirical method for acquiring knowledge that has been referred to while doing science since at least the 17th century. Historically, it was developed through the centuries from the ancient and medieval world. The scientific method involves careful observation coupled with rigorous skepticism, because cognitive assumptions can distort the interpretation of the observation. Scientific inquiry includes creating a testable hypothesis through inductive reasoning, testing it through experiments and statistical analysis, and adjusting or discarding the hypothesis based on the results.

Although procedures vary across fields, the underlying process is often similar. In more detail: the scientific method involves making conjectures (hypothetical explanations), predicting the logical consequences of hypothesis, then carrying out experiments or empirical observations based on those predictions. A hypothesis is a conjecture based on knowledge obtained while seeking answers to the question. Hypotheses can be very specific or broad but must be falsifiable, implying that it is possible to identify a possible outcome of an experiment or observation that conflicts with predictions deduced from the hypothesis; otherwise, the hypothesis cannot be meaningfully tested.

An experiment is a procedure carried out to support or refute a hypothesis, or determine the efficacy or likelihood of something previously untried. Experiments provide insight into cause-and-effect by demonstrating what outcome occurs when a particular factor is manipulated. Experiments vary greatly in goal and scale but always rely on repeatable procedure and logical analysis of the results. There also exist natural experimental studies.

A child may carry out basic experiments to understand how things fall to the ground, while teams of scientists may take years of systematic investigation to advance their understanding of a phenomenon. Experiments and other types of hands-on activities are very important to student learning in the science classroom. Experiments can raise test scores and help a student become more engaged and interested in the material they are learning, especially when used over time. Experiments can vary from personal and informal natural comparisons (e.g. tasting a range of chocolates to find a favorite), to highly controlled (e.g. tests requiring complex apparatus overseen by many scientists that hope to discover information about subatomic particles). Uses of experiments vary considerably between the natural and human sciences.

Models of communication simplify or represent the process of communication. Most communication models try to describe both verbal and non-verbal communication and often understand it as an exchange of messages. Their function is to give a compact overview of the complex process of communication. This helps researchers formulate hypotheses, apply communication-related concepts to real-world cases, and test predictions. Despite their usefulness, many models are criticized based on the claim that they are too simple because they leave out essential aspects. The components and their interactions are usually presented in the form of a diagram. Some basic components and interactions reappear in many of the models. They include the idea that a sender encodes information in the form of a message and sends it to a receiver through a channel. The receiver needs to decode the message to understand the initial idea and provides some form of feedback. In both cases, noise may interfere and distort the message.

Models of communication are classified depending on their intended applications and on how they conceptualize the process. General models apply to all forms of communication while specialized models restrict themselves to specific forms, like mass communication. Linear transmission models understand communication as a one-way process in which a sender transmits an idea to a receiver. Interaction models include a feedback loop through which the receiver responds after getting the message. Transaction models see sending and responding as simultaneous activities. They hold that meaning is created in this process and does not exist prior to it. Constitutive and constructionist models stress that communication is a basic phenomenon responsible for how people understand and experience reality. Interpersonal models describe communicative exchanges with other people. They contrast with intrapersonal models, which discuss communication with oneself. Models of non-human communication describe communication among other species. Further types include encoding-decoding models, hypodermic models, and relational models.

Abiogenesis or the origin of life (sometimes called biopoesis) is the natural process by which life arises from non-living matter, such as simple organic compounds. The prevailing scientific hypothesis is that the transition from non-living to living entities on Earth was not a single event, but a process of increasing complexity involving the formation of a habitable planet, the prebiotic synthesis of organic molecules, molecular self-replication, self-assembly, autocatalysis, and the emergence of cell membranes. The transition from non-life to life has not been observed experimentally, but many proposals have been made for different stages of the process.

The study of abiogenesis aims to determine how pre-life chemical reactions gave rise to life under conditions strikingly different from those on Earth today. It uses tools from biology and chemistry, attempting a synthesis of many sciences. Life functions through the chemistry of carbon and water, and builds on four chemical families: lipids for cell membranes, carbohydrates such as sugars, amino acids for protein metabolism, and the nucleic acids DNA and RNA for heredity. A theory of abiogenesis must explain the origins and interactions of these classes of molecules.

Orthogenesis, also known as orthogenetic evolution, progressive evolution, evolutionary progress, or progressionism, is an obsolete biological hypothesis that organisms have an innate tendency to evolve in a definite direction towards some goal (teleology) due to some internal mechanism or "driving force". According to the theory, the largest-scale trends in evolution have an absolute goal such as increasing biological complexity. Prominent historical figures who have championed some form of evolutionary progress include Jean-Baptiste Lamarck, Pierre Teilhard de Chardin, and Henri Bergson.

The term orthogenesis was introduced by Wilhelm Haacke in 1893 and popularized by Theodor Eimer five years later. Proponents of orthogenesis had rejected the theory of natural selection as the organizing mechanism in evolution for a rectilinear (straight-line) model of directed evolution. With the emergence of the modern synthesis, in which genetics was integrated with evolution, orthogenesis and other alternatives to Darwinism were largely abandoned by biologists, but the notion that evolution represents progress is still widely shared; modern supporters include E. O. Wilson and Simon Conway Morris. The evolutionary biologist Ernst Mayr made the term effectively taboo in the journal Nature in 1948, by stating that it implied "some supernatural force". The American paleontologist George Gaylord Simpson (1953) attacked orthogenesis, linking it with vitalism by describing it as "the mysterious inner force". Despite this, many museum displays and textbook illustrations continue to give the impression that evolution is directed.

Pseudoscience consists of statements, beliefs, or practices that claim to be scientific or factual but are inherently incompatible with the scientific method. Pseudoscience is often characterized by contradictory, exaggerated or unfalsifiable claims; reliance on confirmation bias rather than rigorous attempts at refutation; lack of openness to evaluation by other experts; absence of systematic practices when developing hypotheses; and continued adherence long after the pseudoscientific hypotheses have been experimentally discredited. It is not the same as junk science.

The demarcation between science and pseudoscience has scientific, philosophical, and political implications. Philosophers debate the nature of science and the general criteria for drawing the line between scientific theories and pseudoscientific beliefs, but there is widespread agreement "that creationism, astrology, homeopathy, Kirlian photography, dowsing, ufology, ancient astronaut theory, Holocaust denialism, Velikovskian catastrophism, and climate change denialism are pseudosciences." There are implications for health care, the use of expert testimony, and weighing environmental policies. Recent empirical research has shown that individuals who indulge in pseudoscientific beliefs generally show lower evidential criteria, meaning they often require significantly less evidence before coming to conclusions. This can be coined as a 'jump-to-conclusions' bias that can increase the spread of pseudoscientific beliefs. Addressing pseudoscience is part of science education and developing scientific literacy.

In statistics, a population is a set of similar items or events which is of interest for some question or experiment. A statistical population can be a group of existing objects (e.g. the set of all stars within the Milky Way galaxy) or a hypothetical and potentially infinite group of objects conceived as a generalization from experience (e.g. the set of all possible hands in a game of poker). A population with finitely many values ${\displaystyle N}$ in the support of the population distribution is a finite population with population size ${\displaystyle N}$. A population with infinitely many values in the support is called infinite population.

A common aim of statistical analysis is to produce information about some chosen population.In statistical inference, a subset of the population (a statistical sample) is chosen to represent the population in a statistical analysis. Moreover, the statistical sample must be unbiased and accurately model the population. The ratio of the size of this statistical sample to the size of the population is called a sampling fraction. It is then possible to estimate the population parameters using the appropriate sample statistics.

The theory of consumer choice is the branch of microeconomics that relates preferences to consumption expenditures and to consumer demand curves. It analyzes how consumers maximize the desirability of their consumption (as measured by their preferences subject to limitations on their expenditures), by maximizing utility subject to a consumer budget constraint.Factors influencing consumers' evaluation of the utility of goods include: income level, cultural factors, product information and physio-psychological factors.

Consumption is separated from production, logically, because two different economic agents are involved. In the first case, consumption is determined by the individual. Their specific tastes or preferences determine the amount of utility they derive from goods and services they consume. In the second case, a producer has different motives to the consumer in that they are focussed on the profit they make. This is explained further by producer theory. The models that make up consumer theory are used to represent prospectively observable demand patterns for an individual buyer on the hypothesis of constrained optimization. Prominent variables used to explain the rate at which the good is purchased (demanded) are the price per unit of that good, prices of related goods, and wealth of the consumer.

Paranormal events are purported phenomena described in popular culture, folklore, and other non-scientific bodies of knowledge, whose existence within these contexts is described as being beyond the scope of normal scientific understanding. Notable paranormal beliefs include those that pertain to extrasensory perceptions (for example, telepathy), and the pseudosciences of ghost hunting, cryptozoology, and ufology.

Proposals regarding the paranormal are different from scientific hypotheses or speculations extrapolated from scientific evidence because scientific ideas are grounded in empirical observations and experimental data gained through the scientific method. In contrast, those who argue for the existence of the paranormal explicitly do not base their arguments on empirical evidence but rather on anecdote, testimony and suspicion. The standard scientific models give the explanation that what appears to be paranormal phenomena is usually a misinterpretation, misunderstanding or anomalous variation of natural phenomena.

Falsifiability is a standard of evaluation of scientific theories and hypotheses. A hypothesis is falsifiable if it belongs to a language or logical structure capable of describing an empirical observation that contradicts it. It was introduced by the philosopher of science Karl Popper in his book The Logic of Scientific Discovery (1934). Popper emphasized that the contradiction is to be found in the logical structure alone, without having to worry about methodological considerations external to this structure. He proposed falsifiability as the cornerstone solution to both the problem of induction and the problem of demarcation.

Popper also emphasized the related asymmetry created by the relation of a universal law with basic observation statements and contrasted falsifiability with the intuitively similar concept of verifiability that was then current in the philosophical discipline of logical positivism. He argued that the only way to verify a claim such as "All swans are white" would be if one could empirically observe all swans, which is not possible. On the other hand, the observation of a single black swan is enough to refute this claim.